1. Field of the Invention
The invention relates to a system and method for motion detection and the use thereof in video coding. The invention further relates to an apparatus implementing such methods for motion detection with or without combination with video coding.
2. Description of the Related Technology
Motion region detection is one of important early vision tasks for many high-level semantic video processing applications, e.g., automated video surveillance.
Motion region detection is an important vision topic usually tackled by a background subtraction principle, which has some practical restrictions. Traditional background subtraction paradigm [R. J. Radke, S. Andra, O. Al-Kofahi, and B. Roysam, “Image change detection algorithms: a systematic survey,” IEEE Tran. on Image Processing, vol. 14, pp. 294-307, March 2005.] is based on segmenting motion regions based on the trained background models and hence knowledge of the fixed background is required.
By far, many algorithms have been proposed for motion detection and image saliency detection. However, striking a good tradeoff between the detection quality and computational load still remains a challenge. An efficient static region detection scheme (single-scaled approach) is adopted for bi-level video in [J. Li et al., “Bi-level video: video communication at very low bit rates,” in ACM Multimedia, 2001, vol. 9, pp. 392-400.] and can be used in a context with rather simple scenes as in a video conference setting but it can not deal with complicated scenes well or distinguish separate moving objects.
To construct a scale-invariant saliency map from a static image, a hybrid multi-scale approach is proposed in [F. Lius and M. Gleicher, “Region enhanced scale-invariant saliency detection,” in IEEE ICME, 2006, pp. 1477-1480.], and yet it involves a complicated image segmentation stage as well, e.g. based on edge detection within one image. No motion region detection is performed.
The coarse-to-fine strategy in [A. Bevilacqua, L. D. Stefano, A. Lanza, and G. Capelli, “A novel approach to change detection based on a coarse-to-fine strategy,” in IEEE ICIP, 2005, vol. 2, pp. 434-437.] performs a coarse-level detection at a more than 10-times reduced image scale to achieve the computational efficiency, but the detection quality is hence compromised. This application is for image segmentation only, not for motion region detection. Moreover the coarse-to-final strategy, which implicitly uses a sort of multi-scale approach, exploits such scale aspect only for computational efficiency. Moreover, an integrated algorithm fully exploiting the cross-scale interrelation is not presented.